Build an AI Powered Product Feedback Tracker

Here is a step-by-step guide for building an AI Product Feedback Tracker in Stackby.

Build Your Product Feedback Database

Centralize all customer and internal feedback into one structured table to keep it organized and searchable.

• Add fields for Feedback ID, User Name, Feedback Type (Bug, Feature, UX), Priority, Status, Date Submitted.

• This makes it easy to search, filter, and prioritize feedback.

Tables to Create for product feedback tracking

• Feedback Table → Central database for all feedback (linked to users, features, bugs).

• Products Table → List of products/modules with details (useful for mapping feedback).

• Users Table → Customers or internal team members providing feedback.

• Feature Requests Table → Central log of requested features with priority & status.

• Bug Reports Table → Separate table for reported bugs with severity and fix tracking.

• Comments/Discussions Table → To capture internal discussions or customer follow-ups.

Collect Feedback via Forms

Easily capture feedback with embedded forms so customers and teams can submit inputs seamlessly.

• Use Form View to collect structured input.

• Embed the form on your website, app, or internal wiki.

• Capture source of feedback (Support, Email, Survey, App).

Visualize and Track Feedback Status

Use Kanban, Grid, or Calendar views to track progress of feedback from submission to resolution.

• Use Kanban View to track stages (New → Under Review → In Progress → Resolved).

• Create Calendar Views to see feedback submission trends.

• Use Grid Views for grouping and prioritization.

Link Across Tables for Context

Connect feedback to users, features, and bugs to understand context and prioritize effectively.

• Link Feedback → Product Features to know which requests map to roadmap items.

• Link Feedback → Users to see which customer groups are asking for what.

• Link Feedback → Bug Reports for tracking fixes.

Setup Workflow Automations

Automate notifications, assignments, and status updates to reduce manual follow-ups.

• Auto-assign feedback to product managers based on category.

• Notify teams when high-priority bugs are reported

• Build a weekly digest on improved tasks and feedback.

• Trigger status updates when a related feature is marked as complete.

Summarize, Categorize and extract Sentiment with AI

Leverage AI to summarize, categorize, and analyze sentiment for faster decision-making.

• Summarize long feedback into short notes.

• Categorize automatically (Bug, Feature, UX, Performance).

• Extract sentiment (positive, negative, neutral).

• Suggest priority levels based on keywords.

Collaborate and Communicate with your team

Enable teams to discuss, assign, and share key feedback directly in the workspace.

• Assign ownership to specific PMs or teams.

• Use @mentions for internal discussions.

• Share filtered views like “Top Customer Requests” with stakeholders.

Build Product Feedback Dashboards

Turn raw feedback into insights with charts, KPIs, and trends for stakeholders.

• Pivot Tables: Create 2D visualizations across feedback and product areas or staus or sentiment.

• Charts: Feedback by type, status, sentiment, or product area.

• KPs: Average resolution time, % of high-priority feedback closed.

• Row cards: Top features requested or recurring issues.

Monitor, Iterate, and Optimize

Continuously improve by reviewing feedback trends and refining your collection process.

• Review feedback trends quarterly.

• Track which feedback led to product improvements.

• Adjust collection methods to close gaps (e.g., add in-app surveys).